Risk-Sharing and Endogenous Network Formation

risk-sharing, networks, group formation

Risk-sharing networks and insurance against illness

Most risk-sharing tests on developing country data are conducted at the level of the village; generally, the full risk-sharing hypothesis is rejected. This paper uses detailed data on all insurance networks within a village in Tanzania; networks are not clustered but largely overlapping. We test whether full risk-sharing occurs within these networks. We find that even within these smaller networks risk is not fully shared. In the event of a health shock, households reduce overall consumption: they cut back non-food consumption by roughly 30%, while protecting their food consumption.

RISK-SHARING NETWORKS AND INSURANCE AGAINST ILLNESS

Most risk-sharing tests on developing country data are conducted at the level of the village; generally, the full risk-sharing hypothesis is rejected. This paper uses detailed data on all insurance networks within a village in Tanzania; networks are not clustered but largely overlapping. We test whether full risk-sharing occurs within these networks. We find that even within these smaller networks risk is not fully shared. In the event of a health shock, households reduce overall consumption: they cut back non-food consumption by roughly 30%, while protecting their food consumption.full insurance hypothesis, risk-sharing, networks and health shocks

Asymmetry of Information within Family Networks

This paper studies asymmetry of information and transfers within 712 extended family networks from Tanzania. Using cross-reports on asset holdings, we construct measures of mis-perception of living standards among households within the same network. We contrast altruism, pressure, exchange and risk sharing as motives to transfer in simple models with asymmetric information. Testing the model predictions in the data uncovers the active role played by recipients of transfers. Our findings suggest that recipients set the terms of the transfers, either by exerting pressure on donors or because they hold substantial bargaining power in their exchange relationships

Working memory in children with reading and/or mathematical disabilities

Elementary school children with reading disabilities (RD; n = 17), mathematical disabilities (MD; n = 22), or combined reading and mathematical disabilities (RD+MD; n = 28) were compared to average achieving (AA; n = 45) peers on working memory measures. On all working memory components, 2 (RD vs. no RD) x 2 (MD vs. no MD) factorial ANCOVAs revealed clear differences between children with and without RD. Children with MD had lower span scores than the AA children on measures of the phonological loop and the central executive. A significant interaction effect between RD and MD was found only for listening recall and had a small, partial effect size. In addition, analyses showed that the best logistic regression model consisted of a visuospatial and a central executive task. The model significantly distinguished between the AA and clinical groups and between the MD and RD+MD groups. Evidence was found for domain-general working memory problems in children with learning disabilities. Management of working memory loads in structured learning activities in the classroom, at home, or during therapy may help these children to cope with their problems in a more profound manner

Fuzzy argumentation for trust

In an open Multi-Agent System, the goals of agents acting on behalf of their owners often conflict with each other. Therefore, a personal agent protecting the interest of a single user cannot always rely on them. Consequently, such a personal agent needs to be able to reason about trusting (information or services provided by) other agents. Existing algorithms that perform such reasoning mainly focus on the immediate utility of a trusting decision, but do not provide an explanation of their actions to the user. This may hinder the acceptance of agent-based technologies in sensitive applications where users need to rely on their personal agents. Against this background, we propose a new approach to trust based on argumentation that aims to expose the rationale behind such trusting decisions. Our solution features a separation of opponent modeling and decision making. It uses possibilistic logic to model behavior of opponents, and we propose an extension of the argumentation framework by Amgoud and Prade to use the fuzzy rules within these models for well-supported decisions